Children differ in their success in
learning what is taught at school – skills such as reading and mathematics, and
knowledge such as scientific theories and historical facts. To what extent are
these individual differences in educational achievement due to nurture or
nature? As academic skills and knowledge are taught at school but are seldom
explicitly or systematically taught outside of school, it would be reasonable
to assume that differences between students in how much they learn are due to
differences in how well the educational system teaches these skills and
knowledge. From this perspective, it is surprising that quantitative genetic
research such as the twin method, which compares identical and fraternal twins,
indicates that individual differences in educational achievement are
substantially due to genetic differences (heritability) and only modestly due
to differences between schools and other environmental differences [1].
For example, we have recently shown in a UK sample of 7,500 pairs of twins
assessed longitudinally at ages 7, 9 and 12 that individual differences in
literacy and numeracy are significantly and substantially heritable [2].
Across the three ages, the average heritability of literacy and numeracy was
68%, which means that two-thirds of the individual differences (variance) in
children's performance on tests of school achievement can be ascribed to
genetic differences – i.e., inherited differences in DNA sequence – between
them. Remarkably, educational achievement was found to be more heritable than
intelligence (68% versus 42%), even though intelligence is not taught directly
in schools and is generally viewed as an aptitude of individuals rather than an
outcome of schooling.

Although earlier genetic research on
school achievement produced a wide range of estimates of heritability, sampling
issues may have masked a more consistent pattern. For example, a classic twin
study of school achievement found heritabilities of about 40% for English and
mathematics in a study of more than 2000 twin pairs [3].
However, heritability estimates in this study are likely to be underestimates
due to restriction of range, because the sample was restricted to the
highest-achieving high-school twins in the U.S., those who had been nominated
by their schools to compete for the National Merit Scholarship Qualifying Test.
The wide range of heritability estimates in three other twin studies of general
educational achievement is likely to be due to their small sample sizes, which
were underpowered to provide reliable point estimates of heritability: Petrill
et al., 2010 (314 pairs) [4];
Thompson, Detterman, & Plomin, 1991 (278 pairs) [5];
Wainwright, Wright, Luciano, Geffen, & Martin, 2005 (390 pairs) [6].

In addition to the UK study mentioned
above which showed high heritability (68%) for literacy and numeracy (Kovas et
al., in press; 7,500 pairs) [2],
a study of twins in Australia, the US and Scandinavia has reported high
heritability (77%) for reading at age 8 (Byrne et al., 2009; 615 pairs) [7] and
in the US at age 10 (Olson et al., 2011; 489 pairs) [8].
Similarly high heritability (62%) has been reported for science performance in
9-year old twins (Haworth et al., 2008; 2602 pairs) [9].
A Dutch study of 12-year-old twins reported a heritability of 60% for a
national test of educational achievement (Bartels et al., 2002; 691 pairs) [10].
Another study of general educational achievement in 12-year-old twins in the
Netherlands (1,178 pairs) and in the UK (3,102 pairs) did not have zygosity
information (Calvin et al., 2012) [11].
However, these studies estimated identical and fraternal twin resemblance from
the proportion of same-sex and opposite-sex twins, and this procedure yielded
heritability estimates of about 60% in the Dutch sample and 65% in the UK sample.

The purpose of the present study was
to investigate the extent to which the remarkably high heritabilities for
educational achievement in the UK persist to the end of compulsory education.
Unlike many countries such as the US, the UK has a nationwide examination for
educational achievement, called the General Certificate of Secondary Education
(GCSE), which most pupils complete at the end of compulsory education,
typically at age 16. The GCSE provides a valuable test of the hypothesis of
strong genetic influence on educational achievement because the GCSE is
administered nationwide under standardised conditions. Furthermore, the GCSE is
important for individuals, for society, and for government because it is used
to make decisions about further education.

On the basis of the evidence from
earlier school years – most specifically, in our research on educational
achievement in the UK at ages 7, 9 and 12 – we tested the hypothesis that the
high heritability of educational achievement persists to the end of compulsory
education, as assessed by the GCSE at age 16. Additional support for this
hypothesis comes from a recent report extending the analysis of the UK dataset
described above [11] to
total GCSE scores at age 16 [12].
As in the previous report for this dataset, zygosity information was not
available, but estimating identical and fraternal resemblance from the
proportion of same-sex and opposite-sex twins suggested substantial genetic
influence on GCSE scores [12].
Although heritability was not reported because of the absence of zygosity
information, the imputed correlations for identical and fraternal twins suggest
a heritability of about 60%. However, a definitive estimate of the heritability
of educational achievement can only be made on the basis of evidence from twins
with known zygosity, which was achieved by the present study.

Tuesday, 3 December 2013

Report on the outcomes of a consultation looking
at visual intervention with a student identified as being Dyspraxic and dyslexic.

This particular post is I believe of considerable importance; it is a detailed analysis / deconstruction of the response of one individual to changes in the presentation of text on a computer screen. This could have been any adult but the graphs would have different peaks. About half of the students show a negative response to red reduction rather than a positive response. Other posts will supply more general background to the ideas. The comments on visual span are highly relevant to the emerging research that was reported at the Oxford event.

The student was
referred as part of her Disabled Student’s allowance.

The student was
diagnosed as Dyslexic/Dyspraxic.

The
consultation was to ascertain visually associated intervention to ameliorate her difficulties with text.

Content

Background

Focussing issues,
Optical correction

Font size, image size,
reading distance orthoptic/convergence issues.

Reading speed and stamina

Crowding.

Visual span

Screenluminosity and
colour,

Memory issues

Summary of
interventions

Comparisons of eye movementsin default and optimal conditions.

Background information.

The student was first diagnosed with ophthalmic problems
at the age of 7 years. Since then there
has been a progressive change in her prescription which is to be expected.

She has correction for myopia (short sight) and for
astigmatisms in both eyes. The correction for her left eye is greater than for
her right eye.

She has been told that her left eye is suppressed (there is
difficulty processing visual information with data from her left eye. If she
covers her right eye the image is less clear than if she covers her left eye.

When reading for extended periods she often…

Covers her left eye

Turns her head sideways (turning towards the right).

If using a computer, increases the size of the text using the
‘zoom’ facilities on the computer.

Becomes very tired giving her very short work periods and
needing longer and longer rest/recovery times. These work periods are only a
few minutes.

Becomes increasingly, easily distracted.

Experiences upper body and neck discomfort.

The
consultation concentrated on identifying these issues quantitatively and
identifying strategies to reduce/remove these barriers to studying.

Outcomes
of the Consultation.

Focussing issues,
Optical correction

Using her glasses, which she uses continuously, the
correction for her right eye appears to leave distance vision still too difficult.

This implies that the
correction is too weak for distance vision. A bifocal
correction might be a solution.

The astigmatism correction appears to be correct for both
eyes.

The vision from her left eye is still compromised at far and
near as would be expected with monocular visual suppression.

This asymmetry in
visual performance would give rise to distance judging problems at far and
near. This would give ‘clumsiness’ characteristics at far and near which would mimic
dyspraxia.

There is visual data being collected by the left eye which
would assist in distance judging but ‘at near’, when reading or writing.

There
is evidence from the eyetracking data that the
left eye data is further suppressed leading to increased suppression of
the left eye and increased and fluctuating fixation
disparity between the two eyes. This
is reduced by the head turning but not prevented.

The head turning would also give rise to upper body and neck discomfort as
small movements would occur as a reflex
in trying to overcome the diplopia.

She experiences diplopia
(double vision effects) when reading or viewing near objects. The diplopia is
greater if the object is nearer. The further away the object is the less the
diplopia.

Using the larger fonts the distance from the text increases,
reduces this effect.

(Diplopia occurs when
the two eyes are focussed (fixated) at points too far apart (fixation disparity) so that the visual
system is unable to compute a single perception (image). In all people there is
some disparity and this is part of
efficient vision. But if it is too great then the visual system is incapable of
the computation of a single image. This
is referred to as ‘insufficent fusional
reserves.. and is associated with the idea of ‘convergence insufficiency’.

If the system can intermittently ‘fuse the data’ or the
disparity keeps varying and data from
one eye is not continually suppressed then the person gets a perception of
unstable or wobbling text or the whole visual scene appears to wobble…
Oscillopsia. To reduce this effect some people keep ‘wobbling their heads
subconsciously which can give rise to nausea and neck/upper body/back aches.

****************************************************

Reading speed

Changing the
font size affects her reading speed as shown in the graph below. This will be
in response to a combination of the following effects.

Changing reading distance.

Changingcrowding
effects(ability of the system to compute the edges of the letters)

Changing the distance for the eyes to travel between words./
changing the demand on the eye muscles.

The first two of these will affect the number of letters
which she can ‘see’( perceive) in each fixation, her visual span. Recent research has shown this to the controlling factor
in reading speed for many people.

( please remember the reading speed
is a measure of phonological output as a response to changing visual input)

Using the bigger font size increases the image size on her retina, this
would reduce crowding effects and allow the processing of more letters at once
(parallel processing). Too big a letter size will move the target fpor the next
saccade too far into the peripheral retina ( away from the fovea) reducing the
accuracy of the saccade, slowing the reading down.

On default (font 12) the
visual span is averaging 1.60 letters. A person with no difficulties will be
processing 10+ letters per fixation

When using her optimal conditions.
There were initially 3.3 characters per fixation . This is more than a 100% improvement.

In the last line, however, the number of fixations was 14 for 79
charactersThat
is 5.6 letters per fixation.

There is a continual gain in the size of the visual span as
she reads with optimal conditions and this is reflected in the improving
reading rate the more she reads, as in the graph below taken from the
eyetracking data.

We can compare this to changing reading rate when reading in default
conditions in the graph below..

Combining the two graphs makes the
difference in reading performance very clear.

These reading performance graphs reflect the changing visual span as the reading period changes. Visual span can be considered as controlling
reading performance rather than controlled by reading performance. As the visual
system gets ‘stressed’ the visual span decreases to the point where the process
becomes to difficult to make use of the process. This is likely to be a
component of her reading stamina problem.

Memory issues

If a person has a short visual span, then the number of bits of visual data needed to ‘read’ a
sentence will be much greater than for someone with the ‘normal visual span’
.To read and comprehend a sentence
would make a much greater demand for working memory from the ‘central executive’( Alan Baddeley’s
model) leaving reduced resources for
comparison of the concepts intrinsic in the sentence with the concepts in long
term memory. Other /additional memory strategies would be needed. Study time
would need to be greater.

By increasing the visual span, memory difficulties, when reading should
be ameliorated.

The decreasing reading speed in default reading conditions and associated
limited reading stamina consequence, would further limit her total read/study
time.

Reading speed, screen
pixel luminosity

Overall
screen brightness.

There is a relationship for The student between overall screen brightness and reading
performance. This can be seen in the
graph above.

The total amount of light entering her eyes is controlled by her pupil
dilation. This reflex is designed to optimise the rate at which the photons are
captured by the pigment molecules in the cone cells of her retinas; but it is
controlled by ambient lighting intensity. There may be a difference between the
optimal intensity landing on her fovea ( centre of focus of the images on the
retina) and the peripheral retina. We do not know. In her case when font size
has been optimised this is now limiting her reading performance.

158/255 is the brightness used for the rest of the testing..

Changing the green pixel brightness

As the green pixels are dimmed then the rate at which the green pigment
in the green cone cells gets bleached is reduced. This will lead to a change in nerve impulse
generation. Possibly to an increase in crowding effects and reduced visual span
for The student .

Changing the
red pixel brightness

This is
completely different to the effect of changing the green component. Although in
a way we are really still changing the ratio of red : green stimulation.This
ratio is the basis of the colour vision /colour recognition process which must
ultimately be based on changing the impulses per second delivering information
to the visual cortex and hence the mediator in object edge detection..visual
processing.

This graph
shows clearly the mathematical relationship between the ratio of green to red pixel
brightness and the reading performance of The student .

All the
red:green optimisation to this point has been undertaken with the blue value
set at 158 as determined by the initial screen brightness study.

Changing the
blue pixel brightness.

The cone
cells containing the blue sensitive pigment are not found in the centre of the fovea. There is a response to changing the blue
pixel brightness but often very little and there appears to be a change with
use of the background on screen for reading.

There is good research evidence
that the amount of blue light affects the magnocellular system particularly (
see research by John Stein al.). The red/green ratio is likely to be more
associated with the ‘parvocellular system’, the edge detection system; the
system which collects the data to identify the ‘object being looked
at’/receiving attention.

The graph
below shows the effect on one aspect of reading performance (scanning). However, in terms of visual clarity when
using an overlay or reading The student , preferred not to have the blue
reduced. As such a cyan overlay closely mimicking the optimal red green ratio
was provided for her to use with printed material. Looking at the graph about reducing the red,
it must be remembered that if the cyan filter removed too much red then this
‘same colour’ would start to limit her
reading performance, similarly if the cyan did not remove enough red then there
would only be a partial benefit to her.
The computer screen setting will provide the optimal red/ green.

On her
computer screen she has the option of using a low blue ( green looking!) screen or the optimal
red:green screen ( grey/Cyan).

In two
months time a second consultation will determine changes in her visual system’s
need and then precisely coloured prescription glasses mimicking her optimal
screen settings can be provided as an
alternative to overlays or screen colour management.

Summary

The student needs the following interventions to optimise
/maximise her reading performance.

Printed material where possible printed at
font 21.

Where possible all
documents to be provided electronically to enable optimal reading conditions.

To be able to make use
of her cyan overlay whenever appropriate.

In lectures meetings,
to be able to sit to the left of the
main centre of visual attention to minimise distractibility.

At the next
consultation the possible provision of optimally tinted prescription glasses .

Comparison of eye movements using default conditions and
optimal conditions.

With default conditions
the distance between the two graphs keeps changing. Whereas with the optimal
conditions it stays more consistent.

If we look at the more
detailed graphs, shorter time periods the difference between the two conditions
is clearer.

Graph showing the detail of saccades
and fixations by both eyes using optimal conditions for a 2 second period for comparison with a 2 second period using default conditions.

The graph shows that both eyes are in
general working together. If this is
compared with the eye movements when reading on default it is easily seen that
the left eye is hardly saccading.

The
original, article makes very interesting reading especially in the context of
the USA where to even imply the
possibility of a visual component in dyslexia can bring down the ‘wrath of the
IDA’ !

After
re-reading the original article, which I commend everyone to read, the
conclusions seem a bit guarded. I have highlighted components of the abstract
which I feel need much more consideration.

E-readers are fast rivalling
print as a dominant method for reading.
Because they offer accessibility options that are impossible in print, they
are potentially beneficial for those with impairments, such as dyslexia. Yet,
little is known about how the use of these devices influences reading in those
who struggle. Here, we observe reading comprehension and speed in 103 high
school students with dyslexia. Reading on paper was compared with reading on a
small handheld e-reader device, formatted to display few words per line. We found that use of the device
significantly improved speed and comprehension, when compared with
traditional presentations on paper for specific subsets of these individuals: Those who struggled most with phoneme
decoding or efficient sight word reading read more rapidly using the
device, and those with limited VA Spans
gained in comprehension. Prior eye tracking studies demonstrated that short
lines facilitate reading in dyslexia, suggesting that it is the use of short
lines (and not the device per se) that leads to the observed benefits. We
propose that these findings may be understood as a consequence of visual
attention deficits, in some with dyslexia, that make it difficult to allocate
attention to uncrowded text near fixation, as the gaze advances during reading.
Short lines ameliorate this by guiding attention to the uncrowded span.

In the actual paper, they state that
they were comparing reading performance on a font 14 in the print with font 42
on the e reader.

In the actual paper, they state that
they were comparing reading performance on a font 14 in the print with font 42 on the e reader.

Now don’t get
me wrong, but perhaps they should have looked at other font sizes on
paper? They did say that the e reader
allows accessibility options so really they were not really looking at e
readers, but at font size. If you read other postings in this blog, this would
not surprise you at all. The graph on optimal
font size for an individual shows the critical importance of font size.

Each
individual appears to have an optimal font size. For most students in the UK which
myself or my colleagues have seen it is far greater than font 14, the default
used on the printed task.

The ‘pretty ‘graph
above shows how the optimal font size varies in a population of dyslexic
students. The modal size is font 17.
About half the students need a font greater than this. Very few though benefit
from a size greater than 24. This data
is collected from students who have full optometric correction. The range of
font optimal font sizes will reflect issues such as...

Crowding effects associated with cone cell size.

Diffraction issues associated with corneal problems

Other low vision issues not correctible by optometrists.

In other postings there are graphs showing the effects on reading
performance of

Changing the background brightness to the text for individuals

Changing the relative brightness of the red, green and blue
pixels.

These
effects will be affected by the individual’s working cone pigment densities,
how quickly the epithelial cells they are plugged into can re-activate the
pigment molecules after they are bleached, as they read as well as the ability
of the individual’s iris to dilate and constrict to optimise the rate at which
the pigments in general are being bleached.
I could even ‘hypothesize’ that changing the relative stimulation of the
red and green cells, which is the basis of foveal edge detection, will change
the rate of data transfer about those edges to the visual cortex. I challenge anyone to explain it differently!

As such for
each individual there would be a specific ratio which sends the most data per
millisecond and this would provide the best provision of data for phonological
processing, and ‘gaze’ management.

But I am not
a Harvard researcher. So I will have to wait until they catch up.

Tuesday, 12 November 2013

It has been
said that Nystagmus is one of the most common forms of visual disability
experienced by Schoolchildren. The same would then of course be true of all age
groups, since it does not ‘ go away’.

What I have
done in this blog is to try to explain and demonstrate how a ‘nystagmus’
actually affects the biology of reading. I have been privileged in my work with
undergraduates in the UK; working with and assisting many adults who despite
their nystagmus have made it into Higher education. With each one I have had
the opportunity to work with them for several hours in my work with OmniRead
and before that TintaVision.

I have been
able to work with them to reduce the
barriers to studying which their disability creates.

All this work
is done objectively, using a binocular eyetracker which allows me to compare
the actual dynamics of their eye movements as they read to those students with
no reading difficulties.

Together we
then calculate the conditions which will maximise their reading performance, by
careful adjustment of the
parameters which control the visual
system’s ability to collect and transmit visual data as they read. All the optimisation work is done using the
controlled reading environment of a computer screen using the protocols and software developed by OmniRead and before by TintaVision.

Each person
needs their own specific conditions to read the most effectively. When they use these conditions then the way
their eyes collect visual data mimics much more closely the way the most fluent
readers do so.

Enjoy this
posting . Please post comments or ask any questions that will help you further
. There are other postings in the blog which put this work into context.

The graph
below shows the eye movements of a Higher education student in the UK reading
from a computer screen. This is for a period of 14 seconds.

The data was
collected using an infra red eye tracker measuring horizontal eye movement at
300Hz.

Summary

A student
with a nystagmus ….

1. Collects and
transmits a very small amount of visual data per second compared with a fluent
reader.

2. Almost
certainly need to use more computational resources making greater demands on
their central executive for visual processing than a fluent reader.

3. Collects
reducing amounts of visual data per second as the reading time extends.There is
a serious stamina problem.

4. Using
optimised reading conditions increases the amount of visual data collected and
transmitted per second and can improve the quality of the data, thereby
probably reducing the demand for resources from the central executive with the
major benefits ensuing from this.

5. A person with
a nystagmus has difficulty maintaining a
fixation.

A fixation is
when the eye stops to collect the visual data allowing edge detection. The
computation of the data into lines /edges can be converted into visual images matched
against visual images retained in long term memory and enable reading. This is not really ‘ like photography’ as
taught in schools but more like the way
the digital data from a roadside camera
can be used to identify a car number plate. Or the way data is used in object
recognition in airport baggage security systems.

The best way
of seeing what is going on is to compare
the eye movement of a person with a nystagmus with the eye movement of a fluent
reader using a binocular eyetracker.

The graph
above shows the eye movements of a typical fluent reader. If we look at the
graph as sets of stairs, the flat parts of the steps are when the eyes effectively
stop moving for a while ,the fixations,
to collect visual data to do the actual ‘reading’. The vertical lines are when
the eye moves extremely quickly to position the eyes to take the next picture. These fast movements are called saccades.

The longer
vertical lines are the saccades back to the beginning of the next line of text.

There are 9
to 10 fixations during this 2 seconds. I
have marked the fixations in green.

During this 2
seconds of reading, the system is not collecting and transmitting visual data
for around 10 milliseconds per fixation, during the rapid movements.

That is for around 100 milliseconds 5% of the time.

This pattern
of eye movement is really a modified‘nystagmus’.

The nystagmus eye movement
pattern can be considered as a ‘primitive
eye visual search mechanism’
from before a mechanism developed to allow more extended time to collect and
analyse visual data in a more detailed way.
This is partly possible by the development of the types of muscle fibres
found in the muscles which control the eye movement. I need to write a posting
on that !

Let’s now
look again at what happens when a person, with a nystagmus is reading. Look at the
graphs below.

What you can
see is the eyes moving from left to
right ( the wobbly lines moving gradually up the graph) and after 10
seconds a sudden move back to the left of the page.

The left eye appears to be continually ‘wobbling’. The right
eye sometimes wobbles, sometimes it does
not. After 11 seconds both eyes start to
wobble with a much greater amplitude.

During the 10th
second the left eye looks like it is reading moving along the line while the
right eye wobbles. There are 5 wobbles
during this 10th second. What
is important is that the reading pattern by the system does ‘change’ over time;
sometimes the ‘wobble’ is more obvious, sometimes not.

The duration
of the ‘slow stages ( data collection and transmission times) is not consistent.
Sometimes the left eye and sometimes the right eye appears to be collecting /sending
the most data.

The graph
below shows the eye movements after 3 seconds of reading. During these two
seconds the right eye ‘wobbles’ 7 times. The left eye appears to wobble about 5
times while the right eye appears to go through an extended fixation.

If we compare
this to what happens after 11 seconds when the system goes into a more obvious ‘wobble’/nystagmus;
in this 2 seconds there are 6 ‘wobbles’.

Most people when
reading take three or four pictures per second, so that is effectively the same
as the number of ‘wobbles our student
was experiencing.

If we look at
the amount of time being spent actually collecting and sending visual data to
the ‘brain’, you can see quite clearly that the left and right eye are able to
send different amounts of data and that the
two eyes although acting ‘sort of together’ are to some extent out of
step, or phase, with each other.

In the first
few seconds of reading by the student with the nystagmus….

the ‘green’ (data transmission)
time is far less than the 95% of time
for the fluent reader.

1. The fast
movements are slower than for the fluent reader.

2. The ‘slow’ stages are very unstable and
actually hardly stop at all, so that the ‘computing of steady images will be more demanding on
the central executive leaving fewer resources to make sense of the ideas in the text.

(Please note
though that for even for a fluent reader, when you look really carefully at the
eyes during fixations, the eyes do not actually stop. There have to be small
movements continuously or they stop collecting and sending data; but these are
very small movements.)

The graph of
the reading after 11 seconds, shows that the ‘slow movement (visual data
collection and transmission time) is becoming more restricted. Increasing the demand on the visual processing
system.

Now consider what happens in terms of vision
during the nystagmus eye movements.

There is no
data transmission from retina to ‘the brain’ while the eyes are travelling
rapidly,during the saccades. The
transmission only takes place during the moments when the eye is ‘stationary’(
the fixations) OR during the slow phases of the nystagmus eye movement, as the
eye changes direction.

In the graphs
for the student with nystagmus above the slowest phases the eye effectively
stops. Often it seems to ‘stall’ as if it is being ‘held back’ as if there is a
feedback inhibiting the ‘fast movement’ or saccade.

There is a
mechanism for ‘fixing’ but the feedback seems very weak and variable.

The following graphs were made
using data when the student was reading using optimised conditions.

The first
graph shows all the data collected by the binocular eyetracker with a period of
about 2 seconds before they saw the text. This shows the ‘typical eye movement
of a person with a nystagmus. There is then a period of around 12 seconds of
reading ,when the eye movements are much more organised, starting to look much more
like those of a fluent reader. This
reading period is followed by 3 seconds when the text has been removed from the
computer screen. The eye movements revert to the typical nystagmus ‘style’.

Using the
optimised conditions the visual data collection and transmission time ( green sections) is a far
greater proportion of the time. There
are now quite clear ( although still unstable) fixations. The fast movement phases are ‘faster’ and a
much smaller proportion of the reading time.